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Ancient-Bench reveals that even advanced models fail to solve the challenges of recognizing ancient Chinese texts, underscoring a critical gap in AI capabilities.
GASE reduces the sim-to-real performance gap to under 10% while outperforming existing methods in segmentation accuracy by over 10%.
FEnc2 achieves up to 228.83x speedup in private inference by revolutionizing how data is packed and processed in Fully Homomorphic Encryption.
Ling-2.6 and Ring-2.6 achieve unprecedented efficiency in agentic intelligence, enabling instant responses and deep reasoning at trillion-parameter scale.
Forget hand-crafted reward functions: $\text{RLR}^3$ leverages rubrics and LLMs to provide fine-grained, multi-criteria supervision, outperforming standard RLVR in vision-language tasks.
